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def run ( app : web . Application ) : """Runs the application in an async context . This function will block indefinitely until the application is shut down . Args : app ( web . Application ) : The Aiohttp Application as created by ` create _ app ( ) `"""
host = app [ 'config' ] [ 'host' ] port = app [ 'config' ] [ 'port' ] # starts app . run _ app ( ) will automatically start the async context . web . run_app ( app , host = host , port = port )
def mavlink_packet ( self , m ) : '''handle an incoming mavlink packet'''
if not self . mpstate . map : # don ' t draw if no map return if m . get_type ( ) != 'GIMBAL_REPORT' : return needed = [ 'ATTITUDE' , 'GLOBAL_POSITION_INT' ] for n in needed : if not n in self . master . messages : return # clear the camera icon self . mpstate . map . add_object ( mp_slipmap . SlipClearLayer ( 'GimbalView' ) ) gpi = self . master . messages [ 'GLOBAL_POSITION_INT' ] att = self . master . messages [ 'ATTITUDE' ] vehicle_dcm = Matrix3 ( ) vehicle_dcm . from_euler ( att . roll , att . pitch , att . yaw ) rotmat_copter_gimbal = Matrix3 ( ) rotmat_copter_gimbal . from_euler312 ( m . joint_roll , m . joint_el , m . joint_az ) gimbal_dcm = vehicle_dcm * rotmat_copter_gimbal lat = gpi . lat * 1.0e-7 lon = gpi . lon * 1.0e-7 alt = gpi . relative_alt * 1.0e-3 # ground plane ground_plane = Plane ( ) # the position of the camera in the air , remembering its a right # hand coordinate system , so + ve z is down camera_point = Vector3 ( 0 , 0 , - alt ) # get view point of camera when not rotated view_point = Vector3 ( 1 , 0 , 0 ) # rotate view _ point to form current view vector rot_point = gimbal_dcm * view_point # a line from the camera to the ground line = Line ( camera_point , rot_point ) # find the intersection with the ground pt = line . plane_intersection ( ground_plane , forward_only = True ) if pt is None : # its pointing up into the sky return None ( view_lat , view_lon ) = mp_util . gps_offset ( lat , lon , pt . y , pt . x ) icon = self . mpstate . map . icon ( 'camera-small-red.png' ) self . mpstate . map . add_object ( mp_slipmap . SlipIcon ( 'gimbalview' , ( view_lat , view_lon ) , icon , layer = 'GimbalView' , rotation = 0 , follow = False ) )
def gamma_centered ( cls , kpts = ( 1 , 1 , 1 ) , use_symmetries = True , use_time_reversal = True ) : """Convenient static constructor for an automatic Gamma centered Kpoint grid . Args : kpts : Subdivisions N _ 1 , N _ 2 and N _ 3 along reciprocal lattice vectors . use _ symmetries : False if spatial symmetries should not be used to reduce the number of independent k - points . use _ time _ reversal : False if time - reversal symmetry should not be used to reduce the number of independent k - points . Returns : : class : ` KSampling ` object ."""
return cls ( kpts = [ kpts ] , kpt_shifts = ( 0.0 , 0.0 , 0.0 ) , use_symmetries = use_symmetries , use_time_reversal = use_time_reversal , comment = "gamma-centered mode" )
def create_with_validation ( cls , * args , ** kwargs ) : """Factory method that creates and validates the model object before it is saved ."""
ret_val = cls ( * args , ** kwargs ) ret_val . full_clean ( ) ret_val . save ( ) return ret_val
def form_valid ( self , post_form , attachment_formset , ** kwargs ) : """Processes valid forms . Called if all forms are valid . Creates a Post instance along with associated attachments if required and then redirects to a success page ."""
save_attachment_formset = attachment_formset is not None and not self . preview if self . preview : return self . render_to_response ( self . get_context_data ( preview = True , post_form = post_form , attachment_formset = attachment_formset , ** kwargs ) , ) # This is not a preview ; the object is going to be saved self . forum_post = post_form . save ( ) if save_attachment_formset : attachment_formset . post = self . forum_post attachment_formset . save ( ) messages . success ( self . request , self . success_message ) if not self . forum_post . approved : messages . warning ( self . request , self . approval_required_message ) return HttpResponseRedirect ( self . get_success_url ( ) )
def _get_analysis_type ( analysis_types : List [ str ] ) -> str : """Determine the overall analysis type ."""
types_set = set ( analysis_types ) return types_set . pop ( ) if len ( types_set ) == 1 else 'wgs'
def re_run_last_cell ( self ) : """Run the previous cell again ."""
text , line = ( self . get_current_editor ( ) . get_last_cell_as_executable_code ( ) ) self . _run_cell_text ( text , line )
async def post ( self , path , data = { } , send_raw = False , ** params ) : '''sends post request Parameters path : str same as get _ url query : kargs dict additional info to pass to get _ url See Also get _ url : Returns requests . models . Response the response that was given'''
url = self . get_url ( path , ** params ) jstr = json . dumps ( data ) for i in range ( self . tries + 1 ) : try : if send_raw : resp = await self . session . post ( url , data = data , timeout = self . timeout ) else : resp = await self . session . post ( url , data = jstr , timeout = self . timeout ) if await self . _process_resp ( resp ) : return resp else : continue except aiohttp . ClientConnectionError : if i >= self . tries : raise aiohttp . ClientConnectionError ( 'Emby server is probably down' )
def zoomlevel ( self ) : """Retrieves zoomlevel from the output response Returns : zoomlevel ( namedtuple ) : A namedtuple of zoomlevel from the output response"""
resources = self . get_resource ( ) zoomlevel = namedtuple ( 'zoomlevel' , 'zoomLevel' ) try : return [ zoomlevel ( resource [ 'zoomLevel' ] ) for resource in resources ] except TypeError : try : if isinstance ( resources [ 'ElevationData' ] , dict ) : return zoomlevel ( resources [ 'ElevationData' ] [ 'ZoomLevel' ] ) except KeyError : try : if isinstance ( resources [ 'SeaLevelData' ] , dict ) : zoom = resources [ 'SeaLevelData' ] [ 'ZoomLevel' ] return zoomlevel ( zoom ) except KeyError : print ( KeyError )
def get_response ( self ) : """Generate the response block of this request . Careful : it only sets the fields which can be set from the request"""
res = IODWriteMultipleRes ( ) for field in [ "seqNum" , "ARUUID" , "API" , "slotNumber" , "subslotNumber" , "index" ] : res . setfieldval ( field , self . getfieldval ( field ) ) # append all block response res_blocks = [ ] for block in self . getfieldval ( "blocks" ) : res_blocks . append ( block . get_response ( ) ) res . setfieldval ( "blocks" , res_blocks ) return res
def format_filename ( series_name , season_number , episode_numbers , episode_names , extension ) : """Generates a filename based on metadata using configured format . : param str series _ name : name of TV series : param int season _ number : the numeric season of series : param list ( int ) episode _ numbers : the numeric episode of the series : param list ( str ) episode _ names : episode title of the series : param str extension : media file extension : returns : formatted filename using input values and configured format : rtype : str"""
epdata = { 'seriesname' : tc . titlecase ( _replace_series_name ( series_name , cfg . CONF . output_series_replacements ) or '' ) , 'seasonnumber' : season_number , 'episode' : _format_episode_numbers ( episode_numbers ) , 'episodename' : tc . titlecase ( _format_episode_name ( episode_names ) ) , 'ext' : extension , } value = apply_replacements ( cfg . CONF . filename_format_ep % epdata , cfg . CONF . output_filename_replacements ) return _make_valid_filename ( value )
def make_carrier_tone ( freq , db , dur , samplerate , caldb = 100 , calv = 0.1 ) : """Produce a pure tone signal : param freq : Frequency of the tone to be produced ( Hz ) : type freq : int : param db : Intensity of the tone in dB SPL : type db : int : param dur : duration ( seconds ) : type dur : float : param samplerate : generation frequency of tone ( Hz ) : type samplerate : int : param caldb : Reference intensity ( dB SPL ) . Together with calv , provides a reference point for what intensity equals what output voltage level : type caldb : int : param calv : Reference voltage ( V ) . Together with caldb , provides a reference point for what intensity equals what output voltage level : type calv : float : returns : tone , timevals - - the signal and the time index values"""
if samplerate <= 0 : raise ValueError ( "Samplerate must be greater than 0" ) if caldb <= 0 : raise ValueError ( "Calibration dB SPL must be greater than 0" ) npts = int ( dur * samplerate ) amp = ( 10 ** ( ( db - caldb ) / 20 ) * calv ) if USE_RMS : amp *= 1.414213562373 if VERBOSE : print ( "current dB: {}, fs: {}, current frequency: {} kHz, AO Amp: {:.6f}" . format ( db , samplerate , freq / 1000 , amp ) ) print ( "cal dB: {}, V at cal dB: {}" . format ( caldb , calv ) ) tone = amp * np . sin ( ( freq * dur ) * np . linspace ( 0 , 2 * np . pi , npts ) ) timevals = np . arange ( npts ) / samplerate return tone , timevals
def add_var_arg ( self , arg_index ) : """Add a command to the submit file to allow variable ( macro ) arguments to be passed to the executable ."""
try : self . __var_args [ arg_index ] except IndexError : if arg_index != self . __arg_index : raise CondorDAGJobError , "mismatch between job and node var_arg index" self . __var_args . append ( '$(macroargument%s)' % str ( arg_index ) ) self . add_arg ( self . __var_args [ self . __arg_index ] ) self . __arg_index += 1
def merge_deltas ( stmts_in ) : """Gather and merge original Influence delta information from evidence . This function is only applicable to Influence Statements that have subj and obj deltas . All other statement types are passed through unchanged . Polarities and adjectives for subjects and objects respectivey are collected and merged by travesrsing all evidences of a Statement . Parameters stmts _ in : list [ indra . statements . Statement ] A list of INDRA Statements whose influence deltas should be merged . These Statements are meant to have been preassembled and potentially have multiple pieces of evidence . Returns stmts _ out : list [ indra . statements . Statement ] The list of Statements now with deltas merged at the Statement level ."""
stmts_out = [ ] for stmt in stmts_in : # This operation is only applicable to Influences if not isinstance ( stmt , Influence ) : stmts_out . append ( stmt ) continue # At this point this is guaranteed to be an Influence deltas = { } for role in ( 'subj' , 'obj' ) : for info in ( 'polarity' , 'adjectives' ) : key = ( role , info ) deltas [ key ] = [ ] for ev in stmt . evidence : entry = ev . annotations . get ( '%s_%s' % key ) deltas [ key ] . append ( entry if entry else None ) # POLARITY # For polarity we need to work in pairs polarity_pairs = list ( zip ( deltas [ ( 'subj' , 'polarity' ) ] , deltas [ ( 'obj' , 'polarity' ) ] ) ) # If we have some fully defined pairs , we take the most common one both_pols = [ pair for pair in polarity_pairs if pair [ 0 ] is not None and pair [ 1 ] is not None ] if both_pols : subj_pol , obj_pol = max ( set ( both_pols ) , key = both_pols . count ) stmt . subj . delta [ 'polarity' ] = subj_pol stmt . obj . delta [ 'polarity' ] = obj_pol # Otherwise we prefer the case when at least one entry of the # pair is given else : one_pol = [ pair for pair in polarity_pairs if pair [ 0 ] is not None or pair [ 1 ] is not None ] if one_pol : subj_pol , obj_pol = max ( set ( one_pol ) , key = one_pol . count ) stmt . subj . delta [ 'polarity' ] = subj_pol stmt . obj . delta [ 'polarity' ] = obj_pol # ADJECTIVES for attr , role in ( ( stmt . subj . delta , 'subj' ) , ( stmt . obj . delta , 'obj' ) ) : all_adjectives = [ ] for adj in deltas [ ( role , 'adjectives' ) ] : if isinstance ( adj , list ) : all_adjectives += adj elif adj is not None : all_adjectives . append ( adj ) attr [ 'adjectives' ] = all_adjectives stmts_out . append ( stmt ) return stmts_out
def replaceData ( self , offset : int , count : int , string : str ) -> None : """Replace data from offset to count by string ."""
self . _replace_data ( offset , count , string )
def gridOn ( self ) : # noqa : N802 """Control whether the gridline is drawn for this tick ."""
return ( self . _gridOn and ( self . _has_default_loc ( ) or transforms . interval_contains ( self . get_view_interval ( ) , self . get_loc ( ) ) ) )
def as_bulk_queries ( queries , bulk_size ) : """Group a iterable of ( stmt , args ) by stmt into ( stmt , bulk _ args ) . bulk _ args will be a list of the args grouped by stmt . len ( bulk _ args ) will be < = bulk _ size"""
stmt_dict = defaultdict ( list ) for stmt , args in queries : bulk_args = stmt_dict [ stmt ] bulk_args . append ( args ) if len ( bulk_args ) == bulk_size : yield stmt , bulk_args del stmt_dict [ stmt ] for stmt , bulk_args in stmt_dict . items ( ) : yield stmt , bulk_args
def set_fitness ( self , v ) : """Set the fitness to a new node . Returns false in case fitness is not finite"""
base = self . _base self . fitness ( v ) if not np . isfinite ( v . fitness ) : self . del_error ( v ) return False if base . _tr_fraction < 1 : self . fitness_vs ( v ) if not np . isfinite ( v . fitness_vs ) : self . del_error ( v ) return False self . del_error ( v ) return True
def head ( self , * args , ** kwargs ) : """Executes an HTTP HEAD . : Parameters : - ` args ` : Non - keyword arguments - ` kwargs ` : Keyword arguments"""
return self . session . head ( * args , ** self . get_kwargs ( ** kwargs ) )
def collect_from_bundle ( self , bundle : Bundle ) -> Dict [ str , Any ] : """Collect objects where : meth : ` type _ check ` returns ` ` True ` ` from bundles . Bundle subclasses can override objects discovered in superclass bundles ."""
members = { } hierarchy = ( [ bundle ] if not self . discover_from_bundle_superclasses else bundle . _iter_class_hierarchy ( ) ) for bundle in hierarchy : module = self . import_bundle_module ( bundle ) if not module : continue members . update ( self . _collect_from_package ( module ) ) return members
def _find_attrNodeNS ( E , namespaceURI , localName ) : '''Must grab the attribute Node to distinquish between an unspecified attribute ( None ) and one set to empty string ( " " ) . namespaceURI localName'''
attr = E . getAttributeNodeNS ( namespaceURI , localName ) if attr is None : return None try : return attr . value except : pass return E . getAttributeNS ( namespaceURI , localName )
def _find_attrNS ( E , namespaceURI , localName ) : '''namespaceURI localName'''
try : v = E . getAttributeNS ( namespaceURI , localName ) if v : return v except : pass return None
def t_NUMBER ( self , t ) : r'( \ d + ( \ . \ d * ) ? | \ . \ d + ) ( [ eE ] [ + - ] ? \ d + ) ? ( kb | gb | mb | tb | pb | Kb | Gb | Mb | Tb | Pb ) ?'
if re . match ( r'^(\d+(\.\d*)?|\.\d+)([eE][+-]?\d+)?(kb|gb|mb|tb|pb|Kb|Gb|Mb|Tb|Pb)?$' , t . value ) : multiplyer = 1 try : suffix = ( t . value [ - 2 : ] ) . lower ( ) if suffix in [ 'kb' ] : multiplyer = 1024 elif suffix in [ 'mb' ] : multiplyer = 1024 * 1024 elif suffix in [ 'gb' ] : multiplyer = 1024 * 1024 * 1024 elif suffix in [ 'tb' ] : multiplyer = 1024 * 1024 * 1024 * 1024 elif suffix in [ 'pb' ] : multiplyer = 1024 * 1024 * 1024 * 1024 * 1024 if multiplyer > 1 : t . value = t . value [ : - 2 ] except : pass try : f = float ( t . value ) try : e = int ( t . value ) except ValueError : e = f if ( e == f ) : t . value = multiplyer * e else : t . value = multiplyer * f except ValueError : _LOGGER . error ( "el valor %s no es un numero valido" % t . value ) t . value = 0 else : t . type = 'STRING' return t
def cklpf ( filename ) : """Load a CK pointing file for use by the CK readers . Return that file ' s handle , to be used by other CK routines to refer to the file . http : / / naif . jpl . nasa . gov / pub / naif / toolkit _ docs / C / cspice / cklpf _ c . html : param filename : Name of the CK file to be loaded . : type filename : str : return : Loaded file ' s handle . : rtype : int"""
filename = stypes . stringToCharP ( filename ) handle = ctypes . c_int ( ) libspice . cklpf_c ( filename , ctypes . byref ( handle ) ) return handle . value
def generate_sample_sls_module ( env_root , module_dir = None ) : """Generate skeleton Serverless sample module ."""
if module_dir is None : module_dir = os . path . join ( env_root , 'sampleapp.sls' ) generate_sample_module ( module_dir ) for i in [ 'config-dev-us-east-1.json' , 'handler.py' , 'package.json' , 'serverless.yml' ] : shutil . copyfile ( os . path . join ( ROOT , 'templates' , 'serverless' , i ) , os . path . join ( module_dir , i ) , ) LOGGER . info ( "Sample Serverless module created at %s" , module_dir )
def start_log_monitor ( self ) : """Start the log monitor ."""
stdout_file , stderr_file = self . new_log_files ( "log_monitor" ) process_info = ray . services . start_log_monitor ( self . redis_address , self . _logs_dir , stdout_file = stdout_file , stderr_file = stderr_file , redis_password = self . _ray_params . redis_password ) assert ray_constants . PROCESS_TYPE_LOG_MONITOR not in self . all_processes self . all_processes [ ray_constants . PROCESS_TYPE_LOG_MONITOR ] = [ process_info ]
def get_relationships ( self ) : """Gets the relationship list resulting from a search . return : ( osid . relationship . RelationshipList ) - the relationship list raise : IllegalState - list already retrieved * compliance : mandatory - - This method must be implemented . *"""
if self . retrieved : raise errors . IllegalState ( 'List has already been retrieved.' ) self . retrieved = True return objects . RelationshipList ( self . _results , runtime = self . _runtime )
def tabulate_body ( obj , level_keys , v_level_indexes , h_level_indexes , v_level_sort_keys = None , h_level_sort_keys = None , ) : """Args : v _ level _ indexes : A sequence of level indexes . h _ level _ indexes : A sequence of level indexes ."""
v_key_sorted = make_sorter ( v_level_sort_keys , v_level_indexes ) h_key_sorted = make_sorter ( h_level_sort_keys , h_level_indexes ) h_level_keys = [ level_keys [ level ] for level in h_level_indexes ] v_level_keys = [ level_keys [ level ] for level in v_level_indexes ] h_key_tuples = h_key_sorted ( product ( * h_level_keys ) ) v_key_tuples = v_key_sorted ( product ( * v_level_keys ) ) h_size = len ( h_key_tuples ) v_size = len ( v_key_tuples ) table = [ [ MISSING for _ in range ( h_size ) ] for _ in range ( v_size ) ] for h_index , h_keys in enumerate ( h_key_tuples ) : for v_index , v_keys in enumerate ( v_key_tuples ) : key_path = [ None ] * len ( level_keys ) merge_into_by_index ( key_path , h_level_indexes , h_keys ) merge_into_by_index ( key_path , v_level_indexes , v_keys ) for v_level , v_key in zip ( v_level_indexes , v_keys ) : key_path [ v_level ] = v_key item = obj for key in key_path : try : item = item [ key ] except ( IndexError , KeyError ) : break else : # no - break table [ v_index ] [ h_index ] = item return table , v_key_tuples , h_key_tuples
def predict_expectation ( self , X , ancillary_X = None ) : """Predict the expectation of lifetimes , : math : ` E [ T | x ] ` . Parameters X : numpy array or DataFrame a ( n , d ) covariate numpy array or DataFrame . If a DataFrame , columns can be in any order . If a numpy array , columns must be in the same order as the training data . ancillary _ X : numpy array or DataFrame , optional a ( n , d ) covariate numpy array or DataFrame . If a DataFrame , columns can be in any order . If a numpy array , columns must be in the same order as the training data . Returns percentiles : DataFrame the median lifetimes for the individuals . If the survival curve of an individual does not cross 0.5 , then the result is infinity . See Also predict _ median"""
lambda_ , rho_ = self . _prep_inputs_for_prediction_and_return_scores ( X , ancillary_X ) return pd . DataFrame ( ( lambda_ * gamma ( 1 + 1 / rho_ ) ) , index = _get_index ( X ) )
def write_data ( self , data , dstart = None , swap_axes = True ) : """Write ` ` data ` ` to ` file ` . Parameters data : ` array - like ` Data that should be written to ` file ` . dstart : non - negative int , optional Offset in bytes of the start position of the written data . If provided , reshaping and axis swapping of ` ` data ` ` is skipped . For ` ` None ` ` , ` header _ size ` is used . swap _ axes : bool , optional If ` ` True ` ` , use the ` ` ' mapc ' , ' mapr ' , ' maps ' ` ` header entries to swap the axes in the ` ` data ` ` before writing . Use ` ` False ` ` only if the data is already consistent with the final axis order ."""
if dstart is None : shape = self . data_shape dstart = int ( self . header_size ) elif dstart < 0 : raise ValueError ( '`dstart` must be non-negative, got {}' '' . format ( dstart ) ) else : shape = - 1 dstart = int ( dstart ) if dstart < self . header_size : raise ValueError ( 'invalid `dstart`, resulting in absolute ' '`dstart` < `header_size` ({} < {})' '' . format ( dstart , self . header_size ) ) data = np . asarray ( data , dtype = self . data_dtype ) . reshape ( shape ) if swap_axes : # Need to argsort here since ` data _ axis _ order ` tells # " which axis comes from where " , which is the inverse of what the # ` transpose ` function needs . data = np . transpose ( data , axes = np . argsort ( self . data_axis_order ) ) assert data . shape == self . data_storage_shape data = data . reshape ( - 1 , order = 'F' ) self . file . seek ( dstart ) data . tofile ( self . file )
def write_warc ( self , resources = None , dumpfile = None ) : """Write a WARC dump file . WARC support is not part of ResourceSync v1.0 ( Z39.99 2014 ) but is left in this library for experimentation ."""
# Load library late as we want to be able to run rest of code # without this installed try : from warc import WARCFile , WARCHeader , WARCRecord except : raise DumpError ( "Failed to load WARC library" ) wf = WARCFile ( dumpfile , mode = "w" , compress = self . compress ) # Add all files in the resources for resource in resources : wh = WARCHeader ( { } ) wh . url = resource . uri wh . ip_address = None wh . date = resource . lastmod wh . content_type = 'text/plain' wh . result_code = 200 wh . checksum = 'aabbcc' wh . location = self . archive_path ( resource . path ) wf . write_record ( WARCRecord ( header = wh , payload = resource . path ) ) wf . close ( ) warcsize = os . path . getsize ( dumpfile ) self . logging . info ( "Wrote WARC file dump %s with size %d bytes" % ( dumpfile , warcsize ) )
def get_arc ( self , x_start , y , y_curve , x_end ) : """Render individual arc . x _ start ( int ) : X - coordinate of arrow start point . y ( int ) : Y - coordinate of arrow start and end point . y _ curve ( int ) : Y - corrdinate of Cubic Bézier y _ curve point . x _ end ( int ) : X - coordinate of arrow end point . RETURNS ( unicode ) : Definition of the arc path ( ' d ' attribute ) ."""
template = "M{x},{y} C{x},{c} {e},{c} {e},{y}" if self . compact : template = "M{x},{y} {x},{c} {e},{c} {e},{y}" return template . format ( x = x_start , y = y , c = y_curve , e = x_end )
def handle_format_group ( self , field , text ) : """Handle format group ."""
# Handle auto incrementing group indexes if field == '' : if self . auto : field = str ( self . auto_index ) text [ 0 ] = ( _util . FMT_FIELD , field ) self . auto_index += 1 elif not self . manual and not self . auto : self . auto = True field = str ( self . auto_index ) text [ 0 ] = ( _util . FMT_FIELD , field ) self . auto_index += 1 else : raise ValueError ( "Cannot switch to auto format during manual format!" ) elif not self . manual and not self . auto : self . manual = True elif not self . manual : raise ValueError ( "Cannot switch to manual format during auto format!" ) self . handle_group ( field , tuple ( text ) , True )
def _verify_dict ( self , conf ) : """Check that the configuration contains all necessary keys . : type conf : dict : rtype : None : raise SATOSAConfigurationError : if the configuration is incorrect : param conf : config to verify : return : None"""
if not conf : raise SATOSAConfigurationError ( "Missing configuration or unknown format" ) for key in SATOSAConfig . mandatory_dict_keys : if key not in conf : raise SATOSAConfigurationError ( "Missing key '%s' in config" % key ) for key in SATOSAConfig . sensitive_dict_keys : if key not in conf and "SATOSA_{key}" . format ( key = key ) not in os . environ : raise SATOSAConfigurationError ( "Missing key '%s' from config and ENVIRONMENT" % key )
def load_results ( result_files , options , run_set_id = None , columns = None , columns_relevant_for_diff = set ( ) ) : """Version of load _ result for multiple input files that will be loaded concurrently ."""
return parallel . map ( load_result , result_files , itertools . repeat ( options ) , itertools . repeat ( run_set_id ) , itertools . repeat ( columns ) , itertools . repeat ( columns_relevant_for_diff ) )
def _get_client ( self ) : """Swift client Returns : swiftclient . client . Connection : client"""
kwargs = self . _storage_parameters # Handles unsecure mode if self . _unsecure : kwargs = kwargs . copy ( ) kwargs [ 'ssl_compression' ] = False return _swift . client . Connection ( ** kwargs )
def MultimodeCombine ( pupils ) : """Return the instantaneous coherent fluxes and photometric fluxes for a multiway multimode combiner ( no spatial filtering )"""
fluxes = [ np . vdot ( pupils [ i ] , pupils [ i ] ) . real for i in range ( len ( pupils ) ) ] coherentFluxes = [ np . vdot ( pupils [ i ] , pupils [ j ] ) for i in range ( 1 , len ( pupils ) ) for j in range ( i ) ] return fluxes , coherentFluxes
def pip ( self , points , sorted_col = 0 , radius = 0 ) : """Point - in - Polygon for the z = 0 projection . This function enhances the performance of ` ` Polygon . contains ( ) ` ` by verifying only the points which are inside the bounding box of the polygon . To do it fast , it needs the points array to be already sorted by one column . : param points : list of * ( x , y , z ) or ( x , y ) * coordinates of the points to check . ( The z value will not be taken into account ) . : type points : ndarray ( shape = ( N , 2 or 3 ) ) : param sorted _ col : Index of the sorted column ( 0 or 1 ) . : type sorted _ col : int : param radius : Enlarge Polygons domain by a specified quantity . : type radius : float : returns : Which points are inside the polygon . : rtype : ndarray ( dtpye = bool ) . . warning : : By default pip considers that the set of points is currently sorted by the first column . . . warning : : This method only works if the polygon has been locked ( : func : ` lock ` ) ."""
xy = points [ : , : 2 ] n_points = xy . shape [ 0 ] index = np . arange ( n_points , dtype = int ) b = self . domain b [ 0 ] = b [ 0 ] - radius b [ 1 ] = b [ 1 ] + radius # Slicing the sorted column k = np . searchsorted ( xy [ : , sorted_col ] , ( b [ 0 , sorted_col ] , b [ 1 , sorted_col ] + 1e-10 ) ) xy = xy [ k [ 0 ] : k [ 1 ] ] index = index [ k [ 0 ] : k [ 1 ] ] # solution k = index [ self . path . contains_points ( xy , radius = radius ) ] sol = np . zeros ( n_points , dtype = bool ) sol [ k ] = True return sol
def execute ( self , container , start = None , end = None , registers = None ) : """Execute instructions ."""
if registers : self . __cpu . registers = dict ( registers ) ip = start if start else container [ 0 ] . address while ip and ip != end : try : instr = container . fetch ( ip ) except ReilContainerInvalidAddressError : logger . info ( "Invalid address: {:#010x}:{:#02x}" . format ( ip >> 8 , ip & 0xff ) ) raise ReilCpuInvalidAddressError ( ) next_ip = self . __execute_one ( instr ) ip = next_ip if next_ip else container . get_next_address ( ip ) return dict ( self . __cpu . registers ) , self . __mem
def _partition_and_stitch ( self , args , func_name ) : """args is a list of tensors , to be passed to self . likelihoods . < func _ name > args [ - 1 ] is the ' Y ' argument , which contains the indexes to self . likelihoods . This function splits up the args using dynamic _ partition , calls the relevant function on the likelihoods , and re - combines the result ."""
# get the index from Y Y = args [ - 1 ] ind = Y [ : , - 1 ] ind = tf . cast ( ind , tf . int32 ) Y = Y [ : , : - 1 ] args [ - 1 ] = Y # split up the arguments into chunks corresponding to the relevant likelihoods args = zip ( * [ tf . dynamic_partition ( X , ind , self . num_likelihoods ) for X in args ] ) # apply the likelihood - function to each section of the data with params_as_tensors_for ( self , convert = False ) : funcs = [ getattr ( lik , func_name ) for lik in self . likelihood_list ] results = [ f ( * args_i ) for f , args_i in zip ( funcs , args ) ] # stitch the results back together partitions = tf . dynamic_partition ( tf . range ( 0 , tf . size ( ind ) ) , ind , self . num_likelihoods ) results = tf . dynamic_stitch ( partitions , results ) return results
def start_task ( self , task_tag , skip_unresolved = False ) : """Check dependency for the given task _ tag and start task . For dependency checking see : meth : ` . WTaskDependencyRegistryStorage . dependency _ check ` . If task is already started then it must be stopped before it will be started again . : param task _ tag : task to start . Any required dependencies will be started automatically . : param skip _ unresolved : flag controls this method behaviour for tasks that could not be found . When False , method will raise an exception if task tag was set in dependency and the related task wasn ' t found in registry . When True that unresolvable task will be omitted : return : None"""
if self . started_tasks ( task_registry_id = task_tag ) is not None : return task_cls = self . tasks_by_tag ( task_tag ) if task_cls is None : raise RuntimeError ( "Task '%s' wasn't found" % task_tag ) self . dependency_check ( task_cls , skip_unresolved = skip_unresolved ) def start_dependency ( start_task_cls ) : for dependency in start_task_cls . __dependency__ : if self . started_tasks ( task_registry_id = dependency ) is not None : continue dependent_task = self . tasks_by_tag ( dependency ) if dependent_task is not None : start_dependency ( dependent_task ) self . __started . append ( start_task_cls . start_dependent_task ( ) ) start_dependency ( task_cls )
def group_records_by_category ( self ) : """Return the records grouped by the category of their source . The return value is a dict , a key in this dict is a category and the value is a list of all the records with this category ."""
Source . validate_categories ( categories ) key_function = lambda record : record . source . category return self . group_records ( key_function )
def get_cpu_info_json ( ) : '''Returns the CPU info by using the best sources of information for your OS . Returns the result in a json string'''
import json output = None # If running under pyinstaller , run normally if getattr ( sys , 'frozen' , False ) : info = _get_cpu_info_internal ( ) output = json . dumps ( info ) output = "{0}" . format ( output ) # if not running under pyinstaller , run in another process . # This is done because multiprocesing has a design flaw that # causes non main programs to run multiple times on Windows . else : from subprocess import Popen , PIPE command = [ sys . executable , __file__ , '--json' ] p1 = Popen ( command , stdout = PIPE , stderr = PIPE , stdin = PIPE ) output = p1 . communicate ( ) [ 0 ] if p1 . returncode != 0 : return "{}" if not IS_PY2 : output = output . decode ( encoding = 'UTF-8' ) return output
def fastq_iter ( handle , header = None ) : """Iterate over FASTQ file and return FASTQ entries Args : handle ( file ) : FASTQ file handle , can be any iterator so long as it it returns subsequent " lines " of a FASTQ entry header ( str ) : Header line of next FASTQ entry , if ' handle ' has been partially read and you want to start iterating at the next entry , read the next FASTQ header and pass it to this variable when calling fastq _ iter . See ' Examples . ' Yields : FastqEntry : class containing all FASTQ data Raises : IOError : If FASTQ entry doesn ' t start with ' @ ' Examples : The following two examples demonstrate how to use fastq _ iter . Note : These doctests will not pass , examples are only in doctest format as per convention . bio _ utils uses pytests for testing . > > > for entry in fastq _ iter ( open ( ' test . fastq ' ) ) : . . . print ( entry . id ) # Print FASTQ id . . . print ( entry . description ) # Print FASTQ description . . . print ( entry . sequence ) # Print FASTQ sequence . . . print ( entry . quality ) # Print FASTQ quality scores . . . print ( entry . write ( ) ) # Print full FASTQ entry > > > fastq _ handle = open ( ' test . fastq ' ) > > > next ( fastq _ handle ) # Skip first entry header > > > next ( fastq _ handle ) # Skip first entry sequence > > > next ( fastq _ handle ) # Skip line with ' + ' > > > next ( fastq _ handle ) # Skip first entry quality scores > > > first _ line = next ( fastq _ handle ) # Read second entry header > > > for entry in fastq _ iter ( fastq _ handle , header = first _ line ) : . . . print ( entry . id ) # Print FASTQ id . . . print ( entry . description ) # Print FASTQ description . . . print ( entry . sequence ) # Print FASTQ sequence . . . print ( entry . quality ) # Print FASTQ quality scores . . . print ( entry . write ( ) ) # Print full FASTQ entry"""
# Speed tricks : reduces function calls append = list . append join = str . join strip = str . strip next_line = next if header is None : header = next ( handle ) # Read first FASTQ entry header # Check if input is text or bytestream if ( isinstance ( header , bytes ) ) : def next_line ( i ) : return next ( i ) . decode ( 'utf-8' ) header = strip ( header . decode ( 'utf-8' ) ) else : header = strip ( header ) try : # Manually construct a for loop to improve speed by using ' next ' while True : # Loop until StopIteration Exception raised line = strip ( next_line ( handle ) ) data = FastqEntry ( ) if not header [ 0 ] == '@' : raise IOError ( 'Bad FASTQ format: no "@" at beginning of line' ) try : data . id , data . description = header [ 1 : ] . split ( ' ' , 1 ) except ValueError : # No description data . id = header [ 1 : ] data . description = '' # obtain sequence sequence_list = [ ] while line and not line [ 0 ] == '+' and not line [ 0 ] == '#' : append ( sequence_list , line ) line = strip ( next_line ( handle ) ) data . sequence = join ( '' , sequence_list ) line = strip ( next_line ( handle ) ) # Skip line containing only ' + ' # Obtain quality scores quality_list = [ ] seq_len = len ( data . sequence ) qual_len = 0 while line and qual_len < seq_len : append ( quality_list , line ) qual_len += len ( line ) line = strip ( next_line ( handle ) ) # Raises StopIteration at EOF header = line # Store current line so it ' s not lost next iteration data . quality = join ( '' , quality_list ) yield data except StopIteration : # Yield last FASTQ entry data . quality = join ( '' , quality_list ) yield data
def start_receive ( self , fd , data = None ) : """Cause : meth : ` poll ` to yield ` data ` when ` fd ` is readable ."""
self . _rfds [ fd ] = ( data or fd , self . _generation ) self . _update ( fd )
def refresh_actions ( self ) : """Create options menu ."""
self . options_menu . clear ( ) # Decide what additional actions to show if self . undocked_window is None : additional_actions = [ MENU_SEPARATOR , self . undock_action , self . close_plugin_action ] else : additional_actions = [ MENU_SEPARATOR , self . dock_action ] # Create actions list self . plugin_actions = self . get_plugin_actions ( ) + additional_actions add_actions ( self . options_menu , self . plugin_actions )
def remapScipy ( im , coords ) : """Remap an image using SciPy . See : func : ` remap ` for parameters ."""
height , width = im . shape [ 0 ] , im . shape [ 1 ] # switch to y , x order coords = coords [ : , : , : : - 1 ] # make it ( h , w , 3 , 3) coords_channels = np . empty ( ( height , width , 3 , 3 ) ) coords_channel = np . zeros ( ( height , width , 3 ) ) coords_channel [ : , : , : 2 ] = coords coords_channels [ : , : , 0 ] = coords_channel coords_channels [ : , : , 1 ] = coords_channel coords_channels [ : , : , 1 , 2 ] = 1 coords_channels [ : , : , 2 ] = coords_channel coords_channels [ : , : , 2 , 2 ] = 2 coords = coords_channels # (3 , h , w , 3) coords = np . rollaxis ( coords , 3 ) return map_coordinates ( im , coords , order = 1 )
def _get_img_attrs ( self , style , kwargs ) : """Get the attributes of an an < img > tag for this image , hidpi - aware"""
# Get the 1x and 2x renditions img_1x , img_2x , size = self . _get_renditions ( kwargs ) return { 'src' : img_1x , 'width' : size [ 0 ] , 'height' : size [ 1 ] , 'srcset' : "{} 1x, {} 2x" . format ( img_1x , img_2x ) if img_1x != img_2x else None , 'style' : ';' . join ( style ) if style else None , 'class' : kwargs . get ( 'class' , kwargs . get ( 'img_class' ) ) , 'id' : kwargs . get ( 'img_id' ) }
def adjust_for_triggers ( self ) : """Remove trigger - related plugins when needed If there are no triggers defined , it ' s assumed the feature is disabled and all trigger - related plugins are removed . If there are triggers defined , and this is a custom base image , some trigger - related plugins do not apply . Additionally , this method ensures that custom base images never have triggers since triggering a base image rebuild is not a valid scenario ."""
triggers = self . template [ 'spec' ] . get ( 'triggers' , [ ] ) remove_plugins = [ ( "prebuild_plugins" , "check_and_set_rebuild" ) , ( "prebuild_plugins" , "stop_autorebuild_if_disabled" ) , ] should_remove = False if triggers and ( self . is_custom_base_image ( ) or self . is_from_scratch_image ( ) ) : if self . is_custom_base_image ( ) : msg = "removing %s from request because custom base image" elif self . is_from_scratch_image ( ) : msg = 'removing %s from request because FROM scratch image' del self . template [ 'spec' ] [ 'triggers' ] should_remove = True elif not triggers : msg = "removing %s from request because there are no triggers" should_remove = True if should_remove : for when , which in remove_plugins : logger . info ( msg , which ) self . dj . remove_plugin ( when , which )
def do_ls ( self , nothing = '' ) : """list files in current remote directory"""
for d in self . dirs : self . stdout . write ( "\033[0;34m" + ( '%s\n' % d ) + "\033[0m" ) for f in self . files : self . stdout . write ( '%s\n' % f )
def _describe_atom ( topology , index ) : """Returns a string describing the given atom : param topology : : param index : : return :"""
at = topology . atom ( index ) if topology . n_chains > 1 : return "%s %i %s %i %i" % ( at . residue . name , at . residue . resSeq , at . name , at . index , at . residue . chain . index ) else : return "%s %i %s %i" % ( at . residue . name , at . residue . resSeq , at . name , at . index )
def _example_broker_queue ( quote_ctx ) : """获取经纪队列 , 输出 买盘卖盘的经纪ID , 经纪名称 , 经纪档位"""
stock_code_list = [ "HK.00700" ] for stk_code in stock_code_list : ret_status , ret_data = quote_ctx . subscribe ( stk_code , ft . SubType . BROKER ) if ret_status != ft . RET_OK : print ( ret_data ) exit ( ) for stk_code in stock_code_list : ret_status , bid_data , ask_data = quote_ctx . get_broker_queue ( stk_code ) if ret_status != ft . RET_OK : print ( bid_data ) exit ( ) print ( "%s BROKER" % stk_code ) print ( ask_data ) print ( "\n\n" ) print ( bid_data ) print ( "\n\n" )
def reset ( self , context ) : """Return a reference , forcing close and discard of the underlying connection . Used for ' meta : reset _ connection ' or when some other error is detected ."""
LOG . debug ( '%r.reset(%r)' , self , context ) self . _lock . acquire ( ) try : self . _shutdown_unlocked ( context ) finally : self . _lock . release ( )
def is_interesting ( entry ) : """Is this entry interesting ? ` ` entry ` ` is an XML node representing one entry of the svn status XML output . It looks like this : : < entry path = " unchanged . txt " > < wc - status item = " normal " revision = " 1 " props = " none " > < commit revision = " 1 " > < author > mg < / author > < date > 2015-02-06T07:52:38.163516Z < / date > < / commit > < / wc - status > < / entry > < entry path = " added - but - not - committed . txt " > < wc - status item = " added " revision = " - 1 " props = " none " > < / wc - status > < / entry > < entry path = " ext " > < wc - status item = " external " props = " none " > < / wc - status > < / entry > < entry path = " unknown . txt " > < wc - status props = " none " item = " unversioned " > < / wc - status > < / entry >"""
if entry . get ( 'path' ) == '.' : return False status = entry . find ( 'wc-status' ) if status is None : warning ( 'svn status --xml parse error: <entry path="%s"> without' ' <wc-status>' % entry . get ( 'path' ) ) return False # For SVN externals we get two entries : one mentioning the # existence of the external , and one about the status of the external . if status . get ( 'item' ) in ( 'unversioned' , 'external' ) : return False return True
def port_profile_vlan_profile_switchport_access_mac_group_vlan_classification_access_vlan_access_mac_group ( self , ** kwargs ) : """Auto Generated Code"""
config = ET . Element ( "config" ) port_profile = ET . SubElement ( config , "port-profile" , xmlns = "urn:brocade.com:mgmt:brocade-port-profile" ) name_key = ET . SubElement ( port_profile , "name" ) name_key . text = kwargs . pop ( 'name' ) vlan_profile = ET . SubElement ( port_profile , "vlan-profile" ) switchport = ET . SubElement ( vlan_profile , "switchport" ) access_mac_group_vlan_classification = ET . SubElement ( switchport , "access-mac-group-vlan-classification" ) access = ET . SubElement ( access_mac_group_vlan_classification , "access" ) vlan = ET . SubElement ( access , "vlan" ) access_vlan_id_key = ET . SubElement ( vlan , "access-vlan-id" ) access_vlan_id_key . text = kwargs . pop ( 'access_vlan_id' ) access_mac_group = ET . SubElement ( vlan , "access-mac-group" ) access_mac_group . text = kwargs . pop ( 'access_mac_group' ) callback = kwargs . pop ( 'callback' , self . _callback ) return callback ( config )
def register_app_activity ( ) : """Create watchers for models defined in settings . py . Once created , they will be passed over Activity . objects . follow _ model ( ) , which lives in managers . py"""
from django . conf import settings from django . contrib . contenttypes . models import ContentType from . models import Activity # TO - DO : Add check for existence of setting if not hasattr ( settings , 'ACTIVITY_MONITOR_MODELS' ) : return for item in settings . ACTIVITY_MONITOR_MODELS : try : app_label , model = item [ 'model' ] . split ( '.' , 1 ) content_type = ContentType . objects . get ( app_label = app_label , model = model ) model = content_type . model_class ( ) Activity . objects . follow_model ( model ) except ContentType . DoesNotExist : pass
def change_column_length ( table : Table , column : Column , length : int , engine : Engine ) -> None : """Change the column length in the supplied table"""
if column . type . length < length : print ( "Changing length of {} from {} to {}" . format ( column , column . type . length , length ) ) column . type . length = length column_name = column . name column_type = column . type . compile ( engine . dialect ) engine . execute ( 'ALTER TABLE {table} ALTER COLUMN {column_name} TYPE {column_type}' . format ( ** locals ( ) ) )
def ibis_schema_apply_to ( schema , df ) : """Applies the Ibis schema to a pandas DataFrame Parameters schema : ibis . schema . Schema df : pandas . DataFrame Returns df : pandas . DataFrame Notes Mutates ` df `"""
for column , dtype in schema . items ( ) : pandas_dtype = dtype . to_pandas ( ) col = df [ column ] col_dtype = col . dtype try : not_equal = pandas_dtype != col_dtype except TypeError : # ugh , we can ' t compare dtypes coming from pandas , assume not equal not_equal = True if not_equal or dtype == dt . string : df [ column ] = convert ( col_dtype , dtype , col ) return df
def calc_wada_waes_v1 ( self ) : """Calculate the actual water release from the snow cover . Required control parameters : | NHRU | | Lnk | | PWMax | Required flux sequences : | NBes | Calculated flux sequence : | WaDa | Updated state sequence : | WAeS | Basic equations : : math : ` \\ frac { dWAeS } { dt } = NBes - WaDa ` : math : ` WAeS \\ leq PWMax \\ cdot WATS ` Examples : For simplicity , the threshold parameter | PWMax | is set to a value of two for each of the six initialized HRUs . Thus , snow cover can hold as much liquid water as it contains frozen water . Stand precipitation is also always set to the same value , but the initial conditions of the snow cover are varied : > > > from hydpy . models . lland import * > > > parameterstep ( ' 1d ' ) > > > nhru ( 6) > > > lnk ( FLUSS , SEE , ACKER , ACKER , ACKER , ACKER ) > > > pwmax ( 2.0) > > > fluxes . nbes = 1.0 > > > states . wats = 0.0 , 0.0 , 0.0 , 1.0 , 1.0 , 1.0 > > > states . waes = 1.0 , 1.0 , 0.0 , 1.0 , 1.5 , 2.0 > > > model . calc _ wada _ waes _ v1 ( ) > > > states . waes waes ( 0.0 , 0.0 , 0.0 , 2.0 , 2.0 , 2.0) > > > fluxes . wada wada ( 1.0 , 1.0 , 1.0 , 0.0 , 0.5 , 1.0) Note the special cases of the first two HRUs of type | FLUSS | and | SEE | . For water areas , stand precipitaton | NBes | is generally passed to | WaDa | and | WAeS | is set to zero . For all other land use classes ( of which only | ACKER | is selected ) , only the amount of | NBes | exceeding the actual snow holding capacity is passed to | WaDa | ."""
con = self . parameters . control . fastaccess flu = self . sequences . fluxes . fastaccess sta = self . sequences . states . fastaccess for k in range ( con . nhru ) : if con . lnk [ k ] in ( WASSER , FLUSS , SEE ) : sta . waes [ k ] = 0. flu . wada [ k ] = flu . nbes [ k ] else : sta . waes [ k ] += flu . nbes [ k ] flu . wada [ k ] = max ( sta . waes [ k ] - con . pwmax [ k ] * sta . wats [ k ] , 0. ) sta . waes [ k ] -= flu . wada [ k ]
def write_event ( self , event ) : """Appends event to the file ."""
# Check if event is of type event _ pb2 . Event proto . if not isinstance ( event , event_pb2 . Event ) : raise TypeError ( "expected an event_pb2.Event proto, " " but got %s" % type ( event ) ) return self . _write_serialized_event ( event . SerializeToString ( ) )
def process_paper_helper ( model_name , pmid , start_time_local ) : """Wraps processing a paper by either a local or remote service and caches any uncaught exceptions"""
try : if not aws_available : rp , txt_format = process_paper ( model_name , pmid ) else : rp , txt_format = process_paper_aws ( pmid , start_time_local ) except : logger . exception ( 'uncaught exception while processing %s' , pmid ) return None , None return rp , txt_format
async def is_change_done ( self , zone , change_id ) : """Check if a DNS change has completed . Args : zone ( str ) : DNS zone of the change . change _ id ( str ) : Identifier of the change . Returns : Boolean"""
zone_id = self . get_managed_zone ( zone ) url = f'{self._base_url}/managedZones/{zone_id}/changes/{change_id}' resp = await self . get_json ( url ) return resp [ 'status' ] == self . DNS_CHANGES_DONE
def url_encode_stream ( obj , stream = None , charset = 'utf-8' , encode_keys = False , sort = False , key = None , separator = '&' ) : """Like : meth : ` url _ encode ` but writes the results to a stream object . If the stream is ` None ` a generator over all encoded pairs is returned . . . versionadded : : 0.8 : param obj : the object to encode into a query string . : param stream : a stream to write the encoded object into or ` None ` if an iterator over the encoded pairs should be returned . In that case the separator argument is ignored . : param charset : the charset of the query string . : param encode _ keys : set to ` True ` if you have unicode keys . : param sort : set to ` True ` if you want parameters to be sorted by ` key ` . : param separator : the separator to be used for the pairs . : param key : an optional function to be used for sorting . For more details check out the : func : ` sorted ` documentation ."""
gen = _url_encode_impl ( obj , charset , encode_keys , sort , key ) if stream is None : return gen for idx , chunk in enumerate ( gen ) : if idx : stream . write ( separator ) stream . write ( chunk )
def duty_cycle ( self ) : """16 bit value that dictates how much of one cycle is high ( 1 ) versus low ( 0 ) . 0xffff will always be high , 0 will always be low and 0x7fff will be half high and then half low ."""
pwm = self . _pca . pwm_regs [ self . _index ] if pwm [ 0 ] == 0x1000 : return 0xffff return pwm [ 1 ] << 4
def ceil ( self ) : """Round ` x ` and ` y ` up to integers ."""
return Point ( int ( math . ceil ( self . x ) ) , int ( math . ceil ( self . y ) ) )
def ssh_known_host_key ( host , application_name , user = None ) : """Return the first entry in known _ hosts for host . : param host : hostname to lookup in file . : type host : str : param application _ name : Name of application eg nova - compute - something : type application _ name : str : param user : The user that the ssh asserts are for . : type user : str : returns : Host key : rtype : str or None"""
cmd = [ 'ssh-keygen' , '-f' , known_hosts ( application_name , user ) , '-H' , '-F' , host ] try : # The first line of output is like ' # Host xx found : line 1 type RSA ' , # which should be excluded . output = subprocess . check_output ( cmd ) except subprocess . CalledProcessError as e : # RC of 1 seems to be legitimate for most ssh - keygen - F calls . if e . returncode == 1 : output = e . output else : raise output = output . strip ( ) if output : # Bug # 1500589 cmd has 0 rc on precise if entry not present lines = output . split ( '\n' ) if len ( lines ) >= 1 : return lines [ 0 ] return None
def source_attr ( attr_name ) : """Creates a getter that will drop the current value and retrieve the source ' s attribute with specified name . @ param attr _ name : the name of an attribute belonging to the source . @ type attr _ name : str"""
def source_attr ( _value , context , ** _params ) : value = getattr ( context [ "model" ] . source , attr_name ) return _attr ( value ) return source_attr
def neighbors ( self ) : """A dictionary with neighbors The dictionary will have the following form : ` ` { vertexX : ( vertexY1 , vertexY2 , . . . ) , . . . } ` ` This means that vertexX and vertexY1 are connected etc . This also implies that the following elements are part of the dictionary : ` ` { vertexY1 : ( vertexX , . . . ) , vertexY2 : ( vertexX , . . . ) , . . . } ` ` ."""
neighbors = dict ( ( vertex , [ ] ) for vertex in range ( self . num_vertices ) ) for a , b in self . edges : neighbors [ a ] . append ( b ) neighbors [ b ] . append ( a ) # turn lists into frozensets neighbors = dict ( ( key , frozenset ( val ) ) for key , val in neighbors . items ( ) ) return neighbors
def range ( self , dimension , data_range = True , dimension_range = True ) : """Return the lower and upper bounds of values along dimension . Args : dimension : The dimension to compute the range on . data _ range ( bool ) : Compute range from data values dimension _ range ( bool ) : Include Dimension ranges Whether to include Dimension range and soft _ range in range calculation Returns : Tuple containing the lower and upper bound"""
dimension = self . get_dimension ( dimension ) if dimension is None or ( not data_range and not dimension_range ) : return ( None , None ) elif all ( util . isfinite ( v ) for v in dimension . range ) and dimension_range : return dimension . range elif data_range : if dimension in self . kdims + self . vdims : dim_vals = self . dimension_values ( dimension . name ) lower , upper = util . find_range ( dim_vals ) else : dname = dimension . name match_fn = lambda x : dname in x . kdims + x . vdims range_fn = lambda x : x . range ( dname ) ranges = self . traverse ( range_fn , [ match_fn ] ) lower , upper = util . max_range ( ranges ) else : lower , upper = ( np . NaN , np . NaN ) if not dimension_range : return lower , upper return util . dimension_range ( lower , upper , dimension . range , dimension . soft_range )
def handle_line ( self , frame , arg ) : """This function is called when we stop or break at this line ."""
log . info ( 'Stopping at line %s' % pretty_frame ( frame ) ) self . interaction ( frame )
def user_view_task ( self , ) : """View the task that is selected : returns : None : rtype : None : raises : None"""
if not self . cur_user : return i = self . user_task_treev . currentIndex ( ) item = i . internalPointer ( ) if item : task = item . internal_data ( ) if isinstance ( task , djadapter . models . Task ) : self . view_task ( task )
def enable_file_approve ( self , enable = True ) : """Enables or disables menu item ( for entering / leaving save mode )"""
approve_item = self . shortcut2menuitem [ _ ( "&Approve file" ) ] approve_item . Enable ( enable )
def update_groups_for_user ( self , user : User , state : State = None ) : """Update the Group memberships for the given users state : param user : User to update for : param state : State to update user for : return :"""
if state is None : state = user . profile . state for config in self . filter ( states = state ) : # grant user new groups for their state config . update_group_membership_for_user ( user ) for config in self . exclude ( states = state ) : # ensure user does not have groups from previous state config . remove_user_from_alliance_groups ( user ) config . remove_user_from_corp_groups ( user )
def pin_chat_message ( self , * args , ** kwargs ) : """See : func : ` pin _ chat _ message `"""
return pin_chat_message ( * args , ** self . _merge_overrides ( ** kwargs ) ) . run ( )
def _setup_firefox ( self , capabilities ) : """Setup Firefox webdriver : param capabilities : capabilities object : returns : a new local Firefox driver"""
if capabilities . get ( "marionette" ) : gecko_driver = self . config . get ( 'Driver' , 'gecko_driver_path' ) self . logger . debug ( "Gecko driver path given in properties: %s" , gecko_driver ) else : gecko_driver = None # Get Firefox binary firefox_binary = self . config . get_optional ( 'Firefox' , 'binary' ) firefox_options = Options ( ) if self . config . getboolean_optional ( 'Driver' , 'headless' ) : self . logger . debug ( "Running Firefox in headless mode" ) firefox_options . add_argument ( '-headless' ) self . _add_firefox_arguments ( firefox_options ) if firefox_binary : firefox_options . binary = firefox_binary log_path = os . path . join ( DriverWrappersPool . output_directory , 'geckodriver.log' ) try : # Selenium 3 return webdriver . Firefox ( firefox_profile = self . _create_firefox_profile ( ) , capabilities = capabilities , executable_path = gecko_driver , firefox_options = firefox_options , log_path = log_path ) except TypeError : # Selenium 2 return webdriver . Firefox ( firefox_profile = self . _create_firefox_profile ( ) , capabilities = capabilities , executable_path = gecko_driver , firefox_options = firefox_options )
def render ( file ) : """Generate the result HTML ."""
fp = file . open ( ) content = fp . read ( ) fp . close ( ) notebook = nbformat . reads ( content . decode ( 'utf-8' ) , as_version = 4 ) html_exporter = HTMLExporter ( ) html_exporter . template_file = 'basic' ( body , resources ) = html_exporter . from_notebook_node ( notebook ) return body , resources
def xyz2angle ( x , y , z ) : """Convert cartesian to azimuth and zenith ."""
azi = xu . rad2deg ( xu . arctan2 ( x , y ) ) zen = 90 - xu . rad2deg ( xu . arctan2 ( z , xu . sqrt ( x ** 2 + y ** 2 ) ) ) return azi , zen
async def can_cast ( self , unit : Unit , ability_id : AbilityId , target : Optional [ Union [ Unit , Point2 , Point3 ] ] = None , only_check_energy_and_cooldown : bool = False , cached_abilities_of_unit : List [ AbilityId ] = None ) -> bool : """Tests if a unit has an ability available and enough energy to cast it . See data _ pb2 . py ( line 161 ) for the numbers 1-5 to make sense"""
assert isinstance ( unit , Unit ) assert isinstance ( ability_id , AbilityId ) assert isinstance ( target , ( type ( None ) , Unit , Point2 , Point3 ) ) # check if unit has enough energy to cast or if ability is on cooldown if cached_abilities_of_unit : abilities = cached_abilities_of_unit else : abilities = ( await self . get_available_abilities ( [ unit ] ) ) [ 0 ] if ability_id in abilities : if only_check_energy_and_cooldown : return True cast_range = self . _game_data . abilities [ ability_id . value ] . _proto . cast_range ability_target = self . _game_data . abilities [ ability_id . value ] . _proto . target # Check if target is in range ( or is a self cast like stimpack ) if ability_target == 1 or ability_target == Target . PointOrNone . value and isinstance ( target , ( Point2 , Point3 ) ) and unit . distance_to ( target ) <= cast_range : # cant replace 1 with " Target . None . value " because " . None " doesnt seem to be a valid enum name return True # Check if able to use ability on a unit elif ability_target in { Target . Unit . value , Target . PointOrUnit . value } and isinstance ( target , Unit ) and unit . distance_to ( target ) <= cast_range : return True # Check if able to use ability on a position elif ability_target in { Target . Point . value , Target . PointOrUnit . value } and isinstance ( target , ( Point2 , Point3 ) ) and unit . distance_to ( target ) <= cast_range : return True return False
def parse ( self ) -> typing . Union [ list , dict , None ] : """Parse the BYML and get the root node with all children ."""
root_node_offset = self . _read_u32 ( 12 ) if root_node_offset == 0 : return None node_type = self . _data [ root_node_offset ] if not _is_container_type ( node_type ) : raise ValueError ( "Invalid root node: expected array or dict, got type 0x%x" % node_type ) return self . _parse_node ( node_type , 12 )
def sorted_bfs_edges ( G , source = None ) : """Produce edges in a breadth - first - search starting at source . Neighbors appear in the order a linguist would expect in a syntax tree . The result will only contain edges that express a dominance or spanning relation , i . e . edges expressing pointing or precedence relations will be ignored . Parameters G : DiscourseDocumentGraph source : node Specify starting node for breadth - first search and return edges in the component reachable from source . Returns edges : generator A generator of edges in the breadth - first - search ."""
if source is None : source = G . root xpos = horizontal_positions ( G , source ) visited = set ( [ source ] ) source_children = get_child_nodes ( G , source ) queue = deque ( [ ( source , iter ( sorted ( source_children , key = lambda x : xpos [ x ] ) ) ) ] ) while queue : parent , children = queue [ 0 ] try : child = next ( children ) if child not in visited : yield parent , child visited . add ( child ) grandchildren = get_child_nodes ( G , child ) queue . append ( ( child , iter ( sorted ( grandchildren , key = lambda x : xpos [ x ] ) ) ) ) except StopIteration : queue . popleft ( )
def dinfFlowDirection ( self , flow_dir_grid , slope_grid , pit_filled_elevation_grid = None ) : """Calculates flow direction with Dinf method"""
log ( "PROCESS: DinfFlowDirection" ) if pit_filled_elevation_grid : self . pit_filled_elevation_grid = pit_filled_elevation_grid # Construct the taudem command line . cmd = [ os . path . join ( self . taudem_exe_path , 'dinfflowdir' ) , '-fel' , self . pit_filled_elevation_grid , '-ang' , flow_dir_grid , '-slp' , slope_grid , ] self . _run_mpi_cmd ( cmd ) # create projection files self . _add_prj_file ( self . pit_filled_elevation_grid , flow_dir_grid ) self . _add_prj_file ( self . pit_filled_elevation_grid , slope_grid )
def show ( self , filter = None ) : """Print the list of commands currently in the queue . If filter is given , print only commands that match the filter ."""
for command in self . _commands : if command [ 0 ] is None : # or command [ 1 ] in self . _ invalid _ objects : continue # Skip nill commands if filter and command [ 0 ] != filter : continue t = [ ] for e in command : if isinstance ( e , np . ndarray ) : t . append ( 'array %s' % str ( e . shape ) ) elif isinstance ( e , str ) : s = e . strip ( ) if len ( s ) > 20 : s = s [ : 18 ] + '... %i lines' % ( e . count ( '\n' ) + 1 ) t . append ( s ) else : t . append ( e ) print ( tuple ( t ) )
def _set_aaa_config ( self , v , load = False ) : """Setter method for aaa _ config , mapped from YANG variable / aaa _ config ( container ) If this variable is read - only ( config : false ) in the source YANG file , then _ set _ aaa _ config is considered as a private method . Backends looking to populate this variable should do so via calling thisObj . _ set _ aaa _ config ( ) directly ."""
if hasattr ( v , "_utype" ) : v = v . _utype ( v ) try : t = YANGDynClass ( v , base = aaa_config . aaa_config , is_container = 'container' , presence = False , yang_name = "aaa-config" , rest_name = "" , parent = self , path_helper = self . _path_helper , extmethods = self . _extmethods , register_paths = True , extensions = { u'tailf-common' : { u'cli-drop-node-name' : None , u'sort-priority' : u'16' } } , namespace = 'urn:brocade.com:mgmt:brocade-aaa' , defining_module = 'brocade-aaa' , yang_type = 'container' , is_config = True ) except ( TypeError , ValueError ) : raise ValueError ( { 'error-string' : """aaa_config must be of a type compatible with container""" , 'defined-type' : "container" , 'generated-type' : """YANGDynClass(base=aaa_config.aaa_config, is_container='container', presence=False, yang_name="aaa-config", rest_name="", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-drop-node-name': None, u'sort-priority': u'16'}}, namespace='urn:brocade.com:mgmt:brocade-aaa', defining_module='brocade-aaa', yang_type='container', is_config=True)""" , } ) self . __aaa_config = t if hasattr ( self , '_set' ) : self . _set ( )
def fn_minimum_argcount ( callable ) : """Returns the minimum number of arguments that must be provided for the call to succeed ."""
fn = get_fn ( callable ) available_argcount = fn_available_argcount ( callable ) try : return available_argcount - len ( fn . __defaults__ ) except TypeError : return available_argcount
def owner_search_fields ( self ) : """Returns all the fields that are CharFields except for password from the User model . For the built - in User model , that means username , first _ name , last _ name , and email ."""
try : from django . contrib . auth import get_user_model except ImportError : # Django < 1.5 from django . contrib . auth . models import User else : User = get_user_model ( ) return [ field . name for field in User . _meta . fields if isinstance ( field , models . CharField ) and field . name != 'password' ]
def replace_exceptions ( old_to_new_exceptions : Dict [ Type [ BaseException ] , Type [ BaseException ] ] ) -> Callable [ ... , Any ] : """Replaces old exceptions with new exceptions to be raised in their place ."""
old_exceptions = tuple ( old_to_new_exceptions . keys ( ) ) def decorator ( to_wrap : Callable [ ... , Any ] ) -> Callable [ ... , Any ] : @ functools . wraps ( to_wrap ) # String type b / c pypy3 throws SegmentationFault with Iterable as arg on nested fn # Ignore so we don ' t have to import ` Iterable ` def wrapper ( * args : Iterable [ Any ] , ** kwargs : Dict [ str , Any ] ) -> Callable [ ... , Any ] : try : return to_wrap ( * args , ** kwargs ) except old_exceptions as err : try : raise old_to_new_exceptions [ type ( err ) ] from err except KeyError : raise TypeError ( "could not look up new exception to use for %r" % err ) from err return wrapper return decorator
def save_file_list ( key , * files_refs ) : """Convert the given parameters to a special JSON object . Each parameter is a file - refs specification of the form : < file - path > : < reference1 > , < reference2 > , . . . , where the colon ' : ' and the list of references are optional . JSON object is of the form : { key : { " file " : file _ path } } , or { key : { " file " : file _ path , " refs " : [ refs [ 0 ] , refs [ 1 ] , . . . ] } }"""
file_list = [ ] for file_refs in files_refs : if ':' in file_refs : try : file_name , refs = file_refs . split ( ':' ) except ValueError as e : return error ( "Only one colon ':' allowed in file-refs specification." ) else : file_name , refs = file_refs , None if not os . path . isfile ( file_name ) : return error ( "Output '{}' set to a missing file: '{}'." . format ( key , file_name ) ) file_obj = { 'file' : file_name } if refs : refs = [ ref_path . strip ( ) for ref_path in refs . split ( ',' ) ] missing_refs = [ ref for ref in refs if not ( os . path . isfile ( ref ) or os . path . isdir ( ref ) ) ] if len ( missing_refs ) > 0 : return error ( "Output '{}' set to missing references: '{}'." . format ( key , ', ' . join ( missing_refs ) ) ) file_obj [ 'refs' ] = refs file_list . append ( file_obj ) return json . dumps ( { key : file_list } )
def postinit ( self , target = None , value = None ) : """Do some setup after initialisation . : param target : What is being assigned to . : type target : NodeNG or None : param value : The value being assigned to the variable . : type : NodeNG or None"""
self . target = target self . value = value
def setup_job ( manager , job_id , tool_id , tool_version , use_metadata = False ) : """Setup new job from these inputs and return dict summarizing state ( used to configure command line ) ."""
job_id = manager . setup_job ( job_id , tool_id , tool_version ) if use_metadata : manager . enable_metadata_directory ( job_id ) return build_job_config ( job_id = job_id , job_directory = manager . job_directory ( job_id ) , system_properties = manager . system_properties ( ) , tool_id = tool_id , tool_version = tool_version )
def p_expr_XOR_expr ( p ) : """expr : expr XOR expr"""
p [ 0 ] = make_binary ( p . lineno ( 2 ) , 'XOR' , p [ 1 ] , p [ 3 ] , lambda x , y : ( x and not y ) or ( not x and y ) )
def _parse ( self , msg ) : """Parses a Scratch message and returns a tuple with the first element as the message type , and the second element as the message payload . The payload for a ' broadcast ' message is a string , and the payload for a ' sensor - update ' message is a dict whose keys are variables , and values are updated variable values . Returns None if msg is not a message ."""
if not self . _is_msg ( msg ) : return None msg_type = msg [ self . prefix_len : ] . split ( ' ' ) [ 0 ] if msg_type == 'broadcast' : return ( 'broadcast' , self . _parse_broadcast ( msg ) ) else : return ( 'sensor-update' , self . _parse_sensorupdate ( msg ) )
def bishop88 ( diode_voltage , photocurrent , saturation_current , resistance_series , resistance_shunt , nNsVth , d2mutau = 0 , NsVbi = np . Inf , gradients = False ) : """Explicit calculation of points on the IV curve described by the single diode equation [ 1 ] _ . . . warning : : * Do not use ` ` d2mutau ` ` with CEC coefficients . * Usage of ` ` d2mutau ` ` with PVSyst coefficients is required for cadmium - telluride ( CdTe ) and amorphous - silicon ( a : Si ) PV modules only . Parameters diode _ voltage : numeric diode voltages [ V ] photocurrent : numeric photo - generated current [ A ] saturation _ current : numeric diode reverse saturation current [ A ] resistance _ series : numeric series resistance [ ohms ] resistance _ shunt : numeric shunt resistance [ ohms ] nNsVth : numeric product of thermal voltage ` ` Vth ` ` [ V ] , diode ideality factor ` ` n ` ` , and number of series cells ` ` Ns ` ` d2mutau : numeric PVSyst thin - film recombination parameter that is the ratio of thickness of the intrinsic layer squared : math : ` d ^ 2 ` and the diffusion length of charge carriers : math : ` \\ mu \\ tau ` , in volts [ V ] , defaults to 0 [ V ] NsVbi : numeric PVSyst thin - film recombination parameter that is the product of the PV module number of series cells ` ` Ns ` ` and the builtin voltage ` ` Vbi ` ` of the intrinsic layer , in volts [ V ] , defaults to ` ` np . inf ` ` gradients : bool False returns only I , V , and P . True also returns gradients Returns tuple currents [ A ] , voltages [ V ] , power [ W ] , and optionally : math : ` \\ frac { dI } { dV _ d } ` , : math : ` \\ frac { dV } { dV _ d } ` , : math : ` \\ frac { dI } { dV } ` , : math : ` \\ frac { dP } { dV } ` , and : math : ` \\ frac { d ^ 2 P } { dV dV _ d } ` Notes The PVSyst thin - film recombination losses parameters ` ` d2mutau ` ` and ` ` NsVbi ` ` are only applied to cadmium - telluride ( CdTe ) and amorphous - silicon ( a : Si ) PV modules , [ 2 ] _ , [ 3 ] _ . The builtin voltage : math : ` V _ { bi } ` should account for all junctions . For example : tandem and triple junction cells would have builtin voltages of 1.8 [ V ] and 2.7 [ V ] respectively , based on the default of 0.9 [ V ] for a single junction . The parameter ` ` NsVbi ` ` should only account for the number of series cells in a single parallel sub - string if the module has cells in parallel greater than 1. References . . [ 1 ] " Computer simulation of the effects of electrical mismatches in photovoltaic cell interconnection circuits " JW Bishop , Solar Cell ( 1988) : doi : ` 10.1016/0379-6787(88)90059-2 ` . . [ 2 ] " Improved equivalent circuit and Analytical Model for Amorphous Silicon Solar Cells and Modules . " J . Mertens , et al . , IEEE Transactions on Electron Devices , Vol 45 , No 2 , Feb 1998. : doi : ` 10.1109/16.658676 ` . . [ 3 ] " Performance assessment of a simulation model for PV modules of any available technology " , André Mermoud and Thibault Lejeune , 25th EUPVSEC , 2010 : doi : ` 10.4229/25thEUPVSEC2010-4BV . 1.114 `"""
# calculate recombination loss current where d2mutau > 0 is_recomb = d2mutau > 0 # True where there is thin - film recombination loss v_recomb = np . where ( is_recomb , NsVbi - diode_voltage , np . inf ) i_recomb = np . where ( is_recomb , photocurrent * d2mutau / v_recomb , 0 ) # calculate temporary values to simplify calculations v_star = diode_voltage / nNsVth # non - dimensional diode voltage g_sh = 1.0 / resistance_shunt # conductance i = ( photocurrent - saturation_current * np . expm1 ( v_star ) - diode_voltage * g_sh - i_recomb ) v = diode_voltage - i * resistance_series retval = ( i , v , i * v ) if gradients : # calculate recombination loss current gradients where d2mutau > 0 grad_i_recomb = np . where ( is_recomb , i_recomb / v_recomb , 0 ) grad_2i_recomb = np . where ( is_recomb , 2 * grad_i_recomb / v_recomb , 0 ) g_diode = saturation_current * np . exp ( v_star ) / nNsVth # conductance grad_i = - g_diode - g_sh - grad_i_recomb # di / dvd grad_v = 1.0 - grad_i * resistance_series # dv / dvd # dp / dv = d ( iv ) / dv = v * di / dv + i grad = grad_i / grad_v # di / dv grad_p = v * grad + i # dp / dv grad2i = - g_diode / nNsVth - grad_2i_recomb # d2i / dvd grad2v = - grad2i * resistance_series # d2v / dvd grad2p = ( grad_v * grad + v * ( grad2i / grad_v - grad_i * grad2v / grad_v ** 2 ) + grad_i ) # d2p / dv / dvd retval += ( grad_i , grad_v , grad , grad_p , grad2p ) return retval
def send_KeyEvent ( self , key , down ) : """For most ordinary keys , the " keysym " is the same as the corresponding ASCII value . Other common keys are shown in the KEY _ constants ."""
self . sendMessage ( struct . pack ( '!BBxxI' , 4 , down , key ) )
def is_in_scope ( cls , want_scope : str , have_scopes : List [ Scope ] ) -> bool : """Return True if wanted scope is in list of scopes or derived scopes . : param want _ scope : scope wanted for permission to do something ( str because could be invalid scope ) : param have _ scopes : list of valid scopes that user has been assigned"""
if not want_scope : return True if want_scope in have_scopes or want_scope . split ( ':' ) [ 0 ] in have_scopes : return True elif want_scope . startswith ( 'read' ) : return cls . is_in_scope ( want_scope . replace ( 'read' , 'write' ) , have_scopes ) elif want_scope . startswith ( 'write' ) : return cls . is_in_scope ( want_scope . replace ( 'write' , 'admin' ) , have_scopes ) else : return False
def get_host ( self , name , default = NoHostError ) : '''Get a single host by name .'''
if name in self . hosts : return self . hosts [ name ] if default is NoHostError : raise NoHostError ( 'No such host: {0}' . format ( name ) ) return default
def redact_image ( self , parent , inspect_config = None , image_redaction_configs = None , include_findings = None , byte_item = None , retry = google . api_core . gapic_v1 . method . DEFAULT , timeout = google . api_core . gapic_v1 . method . DEFAULT , metadata = None , ) : """Redacts potentially sensitive info from an image . This method has limits on input size , processing time , and output size . See https : / / cloud . google . com / dlp / docs / redacting - sensitive - data - images to learn more . When no InfoTypes or CustomInfoTypes are specified in this request , the system will automatically choose what detectors to run . By default this may be all types , but may change over time as detectors are updated . Example : > > > from google . cloud import dlp _ v2 > > > client = dlp _ v2 . DlpServiceClient ( ) > > > parent = client . project _ path ( ' [ PROJECT ] ' ) > > > response = client . redact _ image ( parent ) Args : parent ( str ) : The parent resource name , for example projects / my - project - id . inspect _ config ( Union [ dict , ~ google . cloud . dlp _ v2 . types . InspectConfig ] ) : Configuration for the inspector . If a dict is provided , it must be of the same form as the protobuf message : class : ` ~ google . cloud . dlp _ v2 . types . InspectConfig ` image _ redaction _ configs ( list [ Union [ dict , ~ google . cloud . dlp _ v2 . types . ImageRedactionConfig ] ] ) : The configuration for specifying what content to redact from images . If a dict is provided , it must be of the same form as the protobuf message : class : ` ~ google . cloud . dlp _ v2 . types . ImageRedactionConfig ` include _ findings ( bool ) : Whether the response should include findings along with the redacted image . byte _ item ( Union [ dict , ~ google . cloud . dlp _ v2 . types . ByteContentItem ] ) : The content must be PNG , JPEG , SVG or BMP . If a dict is provided , it must be of the same form as the protobuf message : class : ` ~ google . cloud . dlp _ v2 . types . ByteContentItem ` retry ( Optional [ google . api _ core . retry . Retry ] ) : A retry object used to retry requests . If ` ` None ` ` is specified , requests will not be retried . timeout ( Optional [ float ] ) : The amount of time , in seconds , to wait for the request to complete . Note that if ` ` retry ` ` is specified , the timeout applies to each individual attempt . metadata ( Optional [ Sequence [ Tuple [ str , str ] ] ] ) : Additional metadata that is provided to the method . Returns : A : class : ` ~ google . cloud . dlp _ v2 . types . RedactImageResponse ` instance . Raises : google . api _ core . exceptions . GoogleAPICallError : If the request failed for any reason . google . api _ core . exceptions . RetryError : If the request failed due to a retryable error and retry attempts failed . ValueError : If the parameters are invalid ."""
# Wrap the transport method to add retry and timeout logic . if "redact_image" not in self . _inner_api_calls : self . _inner_api_calls [ "redact_image" ] = google . api_core . gapic_v1 . method . wrap_method ( self . transport . redact_image , default_retry = self . _method_configs [ "RedactImage" ] . retry , default_timeout = self . _method_configs [ "RedactImage" ] . timeout , client_info = self . _client_info , ) request = dlp_pb2 . RedactImageRequest ( parent = parent , inspect_config = inspect_config , image_redaction_configs = image_redaction_configs , include_findings = include_findings , byte_item = byte_item , ) if metadata is None : metadata = [ ] metadata = list ( metadata ) try : routing_header = [ ( "parent" , parent ) ] except AttributeError : pass else : routing_metadata = google . api_core . gapic_v1 . routing_header . to_grpc_metadata ( routing_header ) metadata . append ( routing_metadata ) return self . _inner_api_calls [ "redact_image" ] ( request , retry = retry , timeout = timeout , metadata = metadata )
def close ( self ) : '''Closes connection with the q service .'''
if self . _connection : self . _connection_file . close ( ) self . _connection_file = None self . _connection . close ( ) self . _connection = None
def pvRvz ( self , vR , vz , R , z , gl = True , ngl = _DEFAULTNGL2 , vTmax = 1.5 ) : """NAME : pvR PURPOSE : calculate the marginalized ( vR , vz ) probability at this location ( NOT normalized by the density ) INPUT : vR - radial velocity ( can be Quantity ) vz - vertical velocity ( can be Quantity ) R - radius ( can be Quantity ) z - height ( can be Quantity ) gl - use Gauss - Legendre integration ( True , currently the only option ) ngl - order of Gauss - Legendre integration vTmax - sets integration limits to [ 0 , vTmax ] for integration over vT ( default : 1.5) OUTPUT : p ( vR , vz , R , z ) HISTORY : 2013-01-02 - Written - Bovy ( IAS ) 2018-01-12 - Added Gauss - Legendre integration prefactor vTmax / 2 - Trick ( MPA )"""
if gl : if ngl % 2 == 1 : raise ValueError ( "ngl must be even" ) # Use Gauss - Legendre integration for all if ngl == _DEFAULTNGL : glx , glw = self . _glxdef , self . _glwdef glx12 , glw12 = self . _glxdef12 , self . _glwdef12 elif ngl == _DEFAULTNGL2 : glx , glw = self . _glxdef2 , self . _glwdef2 glx12 , glw12 = self . _glxdef , self . _glwdef else : glx , glw = numpy . polynomial . legendre . leggauss ( ngl ) glx12 , glw12 = numpy . polynomial . legendre . leggauss ( ngl // 2 ) # Evaluate everywhere vTgl = vTmax / 2. * ( glx + 1. ) vTglw = glw vTfac = 0.5 * vTmax # integration over [ 0 . , vTmax ] # If inputs are arrays , tile if isinstance ( R , numpy . ndarray ) : nR = len ( R ) R = numpy . tile ( R , ( ngl , 1 ) ) . T . flatten ( ) z = numpy . tile ( z , ( ngl , 1 ) ) . T . flatten ( ) vR = numpy . tile ( vR , ( ngl , 1 ) ) . T . flatten ( ) vz = numpy . tile ( vz , ( ngl , 1 ) ) . T . flatten ( ) vTgl = numpy . tile ( vTgl , ( nR , 1 ) ) . flatten ( ) vTglw = numpy . tile ( vTglw , ( nR , 1 ) ) scalarOut = False else : R = R + numpy . zeros ( ngl ) vR = vR + numpy . zeros ( ngl ) z = z + numpy . zeros ( ngl ) vz = vz + numpy . zeros ( ngl ) nR = 1 scalarOut = True # evaluate logqeval = numpy . reshape ( self ( R , vR , vTgl , z , vz , log = True , use_physical = False ) , ( nR , ngl ) ) out = numpy . sum ( numpy . exp ( logqeval ) * vTglw * vTfac , axis = 1 ) if scalarOut : return out [ 0 ] else : return out
def apply_func_to_select_indices_along_full_axis ( self , axis , func , indices , keep_remaining = False ) : """Applies a function to a select subset of full columns / rows . Note : This should be used when you need to apply a function that relies on some global information for the entire column / row , but only need to apply a function to a subset . Important : For your func to operate directly on the indices provided , it must use ` internal _ indices ` as a keyword argument . Args : axis : The axis to apply the function over ( 0 - rows , 1 - columns ) func : The function to apply . indices : The global indices to apply the func to . keep _ remaining : Whether or not to keep the other partitions . Some operations may want to drop the remaining partitions and keep only the results . Returns : A new BaseFrameManager object , the type of object that called this ."""
if self . partitions . size == 0 : return self . __constructor__ ( np . array ( [ [ ] ] ) ) if isinstance ( indices , dict ) : dict_indices = indices indices = list ( indices . keys ( ) ) else : dict_indices = None if not isinstance ( indices , list ) : indices = [ indices ] partitions_dict = self . _get_dict_of_block_index ( axis , indices ) preprocessed_func = self . preprocess_func ( func ) # Since we might be keeping the remaining blocks that are not modified , # we have to also keep the block _ partitions object in the correct # direction ( transpose for columns ) . if not axis : partitions_for_apply = self . column_partitions partitions_for_remaining = self . partitions . T else : partitions_for_apply = self . row_partitions partitions_for_remaining = self . partitions # We may have a command to perform different functions on different # columns at the same time . We attempt to handle this as efficiently as # possible here . Functions that use this in the dictionary format must # accept a keyword argument ` func _ dict ` . if dict_indices is not None : if not keep_remaining : result = np . array ( [ partitions_for_apply [ i ] . apply ( preprocessed_func , func_dict = { idx : dict_indices [ idx ] for idx in partitions_dict [ i ] } , ) for i in partitions_dict ] ) else : result = np . array ( [ partitions_for_remaining [ i ] if i not in partitions_dict else self . _apply_func_to_list_of_partitions ( preprocessed_func , partitions_for_apply [ i ] , func_dict = { idx : dict_indices [ idx ] for idx in partitions_dict [ i ] } , ) for i in range ( len ( partitions_for_apply ) ) ] ) else : if not keep_remaining : # See notes in ` apply _ func _ to _ select _ indices ` result = np . array ( [ partitions_for_apply [ i ] . apply ( preprocessed_func , internal_indices = partitions_dict [ i ] ) for i in partitions_dict ] ) else : # See notes in ` apply _ func _ to _ select _ indices ` result = np . array ( [ partitions_for_remaining [ i ] if i not in partitions_dict else partitions_for_apply [ i ] . apply ( preprocessed_func , internal_indices = partitions_dict [ i ] ) for i in range ( len ( partitions_for_remaining ) ) ] ) return ( self . __constructor__ ( result . T ) if not axis else self . __constructor__ ( result ) )
def from_las ( cls , fname , remap = None , funcs = None , data = True , req = None , alias = None , encoding = None , printfname = False ) : """Constructor . Essentially just wraps ` ` from _ lasio ( ) ` ` , but is more convenient for most purposes . Args : fname ( str ) : The path of the LAS file , or a URL to one . remap ( dict ) : Optional . A dict of ' old ' : ' new ' LAS field names . funcs ( dict ) : Optional . A dict of ' las field ' : function ( ) for implementing a transform before loading . Can be a lambda . printfname ( bool ) : prints filename before trying to load it , for debugging Returns : well . The well object ."""
if printfname : print ( fname ) if re . match ( r'https?://.+\..+/.+?' , fname ) is not None : try : data = urllib . request . urlopen ( fname ) . read ( ) . decode ( ) except urllib . HTTPError as e : raise WellError ( 'Could not retrieve url: ' , e ) fname = ( StringIO ( data ) ) las = lasio . read ( fname , encoding = encoding ) # Pass to other constructor . return cls . from_lasio ( las , remap = remap , funcs = funcs , data = data , req = req , alias = alias , fname = fname )